title: Long term stability of surface EMG pattern classification for prosthetic control.
abstract: Long-term functioning of a hand prosthesis is crucial for its acceptance by patients with upper limb deficit. In this study the reliability over days of the performance of pattern classification approaches based on surface electromyography (sEMG) signal for the control of upper limb prostheses was investigated. Recordings of sEMG from the forearm muscles were obtained across five consecutive days from five healthy subjects. It was demonstrated that the classification performance decreased monotonically on average by 4.1% per day. It was also found that the accumulated error was confined to three of the eight movement classes investigated. This contribution gives insight on the long term behavior of pattern classification, which is crucial for commercial viability.
authors.forename: Sebastian
authors.initials: S
authors.lastname: Amsüss
authors.forename: Liliana P
authors.initials: LP
authors.lastname: Paredes
authors.forename: Nina
authors.initials: N
authors.lastname: Rudigkeit
authors.forename: Bernhard
authors.initials: B
authors.lastname: Graimann
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Herrmann
authors.forename: Dario
authors.initials: D
authors.lastname: Farina
mesh_terms: D000328:Adult; D001186:Artificial Limbs; D004576:Electromyography; D005260:Female; D005542:Forearm / Q000502:physiology; D006801:Humans; D008297:Male; D009119:Muscle Contraction; D010363:Pattern Recognition, Automated / Q000379:methods*; D011474:Prosthesis Design; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors